Engineering Data Science Lab. Department of Industrial and Systems Engineering, KAIST

Research

Statistics · Data Science · Artificial Intelligence · Quality Engineering

Engineering Data Science Lab’s primary research goal is to advance data science methodologies, with a focus on addressing complex real-world challenges and improving the quality of industrial systems.

Publications

J SCIE Journal    C Top-tier AI Conference

2026
C17

GT-PSSM: Unified Probabilistic Framework for Stochastic Dynamics Modeling and Dependency Learning in Multivariate Time Series Anomaly Detection

W. Koo, J. Lee, T. Yoon, and H. Kim

35th International ACM Conference on Knowledge and Information Management (CIKM) , Rome, Italy, November 2026.

CIKM
J64

Knowledge-Assisted Multi-Graph Dependency Learning for Multivariate Time Series Anomaly Detection in Multi-Stage Industrial Processes

J. Lee, T. Yoon, W. Koo, and H. Kim

IEEE Transactions on Automation Science and Engineering, accepted.

IEEE Transactions on Automation Science and Engineering
J63

Order-based Causal Discovery for Multistage Processes

E.-Y. Ma, J. Jung, and H. Kim

IEEE Transactions on Knowledge and Data Engineering, accepted.

IEEE Transactions on Knowledge and Data Engineering
C16

Nonlocal Bayesian Modeling of Continuous Spatio-Temporal Dynamics

J. Lee and H. Kim

Forty-Second Annual Conference on Uncertainty in Artificial Intelligence (UAI), Amsterdam, Netherlands, August 2026.

UAI
C15

Courtroom Analogy: New Perspective on Uncertainty-Aware Classification

T. Yoon and H. Kim

International Conference on Machine Learning (ICML), Seoul, South Korea, July 2026.

ICML
J62

Multimodal Deep Generative Model for Semi-Supervised Learning under Class Imbalance

H. Yoon and H. Kim

Technometrics, https://doi.org/10.1080/00401706.2026.2637593.

Technometrics
2025
C14

Uncertainty Estimation by Flexible Evidential Deep Learning

T. Yoon and H. Kim

Conference on Neural Information Processing Systems (NeurIPS), San Diego, USA, December 2025.

NeurIPS
C13

Learnable Logit Adjustment for Imbalanced Semi-Supervised Learning under Class Distribution Mismatch

H. Lee, T. Park, and H. Kim

International Conference on Computer Vision (ICCV) 2025, Honolulu, Hawaii, USA, October 2025.

ICCV
J61

TSSI: Time Series as Screenshot Images for multivariate time series classification using convolutional neural networks

Y. Oh, H. Kim, and S. Kim

Computers & Industrial Engineering, 209, 111393.

Computers & Industrial Engineering
J60

Simultaneous Treatment Effect Estimation and Variable Selection for Observational Data

E.-Y. Ma, U. Lee, and H. Kim

IISE Transactions, 57(4), 380-392.

IISE Transactions
J59

Multi-task optimization with Bayesian neural network surrogates for parameter estimation of a simulation model

H. Kim, C. Park, and H. Kim

Computational Statistics and Data Analysis, 204, 108097.

Computational Statistics and Data Analysis
2024
C12

Rebalancing Using Estimated Class Distribution for Imbalanced Semi-Supervised Learning under Class Distribution Mismatch

T. Park, H. Lee, and H. Kim

European Conference on Computer Vision (ECCV) 2024, Milan, Italy, September 2024.

ECCV
C11

Uncertainty Estimation by Density Aware Evidential Deep Learning

T. Yoon and H. Kim

International Conference on Machine Learning (ICML), Vienna, Austria, July 2024.

ICML
J58

Few-shot Classification of Wafer Bin Maps Using Transfer Learning and Ensemble Learning

H. Kim, H. Yoon, and H. Kim

ASME Journal of Manufacturing Science and Engineering, 146(7), 070903.

ASME Journal of Manufacturing Science and Engineering
J57

Classification of Chip-level Defect Types in Wafer Bin Maps Using Only Wafer-level Labels

H. Lee, H. Kim, and H. Kim

ASME Journal of Manufacturing Science and Engineering, 146(7), 070902.

ASME Journal of Manufacturing Science and Engineering
C10

CDMAD: Class-Distribution-Mismatch-Aware Debiasing for Class-Imbalanced Semi-Supervised Learning

H. Lee and H. Kim

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2024, Seattle, USA, June 2024.

CVPR
J56

Deep Latent Factor Model for Spatio-Temporal Forecasting

W. Koo, E.-Y. Ma, and H. Kim

Technometrics, 66(3), 470-482. (IISE Quality Control and Reliability Engineering (QCRE) Track Best Paper Competition Finalist)

Technometrics
J55

A Tutorial on Matching-based Causal Analysis of Human Behaviors Using Smartphone Sensor Data

G. Jung, S. Park, E.-Y. Ma, H. Kim, and U. Lee

ACM Computing Surveys, 56(9), 1-33.

ACM Computing Surveys
J54

Simultaneous Classification and Out-of-Distribution Detection for Wafer Bin Maps

J. Choi, E.-Y. Ma, and H. Kim

Quality Engineering, 36(4), 713-725.

Quality Engineering
J53

Simultaneous Deep Clustering and Feature Selection via K-concrete Autoencoder

W. Doo and H. Kim

IEEE Transactions on Knowledge and Data Engineering, 36, 2629-2642.

IEEE Transactions on Knowledge and Data Engineering
J52

Mixed-Type Defect Pattern Recognition in Noisy Labeled Wafer Bin Maps

S. Kim and H. Kim

Quality Engineering, 36(4), 743-757.

Quality Engineering
J51

Spatially-Correlated Time Series Clustering Using Location-Dependent Dirichlet Process Mixture Model

J. Jung, S. Kim, and H. Kim

Statistical Analysis and Data Mining, 17(1), e11649.

Statistical Analysis and Data Mining
2023
J50

Prediction of Highly Imbalanced Semiconductor Chip-Level Defects in Module Tests Using Multimodal Fusion and Logit Adjustment

H. Cho, W. Koo, and H. Kim

IEEE Transactions on Semiconductor Manufacturing, 36(3), 425-433.

IEEE Transactions on Semiconductor Manufacturing
J49

Semi-supervised learning for simultaneous location detection and classification of mixed-type defect patterns in wafer bin maps

H. Lee, J. Lee, and H. Kim

IEEE Transactions on Semiconductor Manufacturing, 36(2), 220-230.

IEEE Transactions on Semiconductor Manufacturing
J48

Contextual anomaly detection for multivariate time series data

H. Kim and H. Kim

Quality Engineering, 35(4), 686-695.

Quality Engineering
C9

Inverse-Reference Priors for Fisher Regularization of Bayesian Neural Networks

K. Kim, E.-Y. Ma, J. Choi, and H. Kim

Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23), Washington, DC, USA, February 2023.

AAAI
J47

Contextual anomaly detection for high-dimensional data using Dirichlet process variational autoencoder

H. Kim and H. Kim

IISE Transactions, 55(5), 433-444.

IISE Transactions
J46

Label-Noise Robust Deep Generative Model for Semi-Supervised Learning

H. Yoon and H. Kim

Technometrics, 65(1), 83-95.

Technometrics
J45

Prediction of highly imbalanced semiconductor chip-level defects using uncertainty-based adaptive margin learning

S. Park, K. Kim, and H. Kim

IISE Transactions, 55(2), 147-155.

IISE Transactions
J44

Deep embedding kernel mixture networks for conditional anomaly detection in high-dimensional data

H. Kim and H. Kim

International Journal of Production Research , 61(4), 1101-1113.

International Journal of Production Research
J43

Toward data-driven digital therapeutics analytics: literature review and research directions

U. Lee, G. Jung, E.-Y. Ma, J. S. Jim, H. Kim, J. Aikhanov, Y. Noh, and H. Kim

IEEE/CAA Journal of Automatica Sinica, 10(1), 42-66.

IEEE/CAA Journal of Automatica Sinica
2022
J42

Deep Gaussian process models for integrating multifidelity experiments with non-stationary relationships

J. Ko and H. Kim

IISE Transactions, 54(7), 686-698. (Selected as a featured article and highlighted in the ISE magazine)

IISE Transactions
J41

Simultaneous band selection and segmentation of hyperspectral images via a mixture of finite maximum margin mixtures

W. Doo and H. Kim

International Journal of Remote Sensing , 43(6), 2296-2314.

International Journal of Remote Sensing
J40

Toward robust battle experimental design for command and control of mechanized infantry brigade

W.-S. Yun, S. Ko, M. Byun, H. Kim, I.-C. Moon, and T.-E. Lee

Military Operations Research, 27(1), 45-72.

Military Operations Research
2021
C8

ABC: Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning

H. Lee, S. Shin, and H. Kim

Conference on Neural Information Processing Systems (NeurIPS) 2021.

NeurIPS
C7

Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models

K. Kim, J. Shin, and H. Kim

Conference on Neural Information Processing Systems (NeurIPS) 2021.

NeurIPS
C6

Objective Bound Conditional Gaussian Process for Bayesian Optimization

T. Jeong and H. Kim

International Conference on Machine Learning (ICML) 2021.

ICML
J39

Robust estimation of sparse precision matrix using adaptive weighted graphical Lasso approach

P. Tang, H. Jiang, H. Kim, and X. Deng

Journal of Nonparametric Statistics, 33, 249-272.

Journal of Nonparametric Statistics
J38

Bayesian Variable Selection in Clustering High-Dimensional Data via a Mixture of Finite Mixtures

W. Doo and H. Kim

Journal of Statistical Computation and Simulation, 91, 2551-2568.

Journal of Statistical Computation and Simulation
J37

Combined unsupervised-supervised machine learning for phenotyping complex diseases with its application to obstructive sleep apnea

E.-Y. Ma, J.-W. Kim, Y. Lee, S.-W. Cho, H. Kim, and J. K. Kim

Scientific Reports, 11, 4457.

Scientific Reports
2020
C5

OOD-MAML: Meta-Learning for Few-Shot Out-of-Distribution Detection and Classification

T. Jeong and H. Kim

Conference on Neural Information Processing Systems (NeurIPS) 2020.

NeurIPS
J36

Semi-Supervised Multi-Label Learning for Classification of Wafer Bin Maps with Mixed-Type Defect Patterns

H. Lee and H. Kim

IEEE Transactions on Semiconductor Manufacturing , 33(4), 653-662.

IEEE Transactions on Semiconductor Manufacturing
J35

Multiresolution spatial generalized linear mixed model for integrating multi-fidelity spatial count data without common identifiers between data sources

S. Kim, R. Duan, G.-Q. Ma, and H. Kim

Spatial Statistics , 39, 100467.

Spatial Statistics
J34

Memory-augmented convolutional neural networks with triplet loss for imbalanced wafer defect pattern classification

Y. Hyun and H. Kim

IEEE Transactions on Semiconductor Manufacturing, 33(4), 622-634.

IEEE Transactions on Semiconductor Manufacturing
J33

Bayesian nonparametric latent class model for longitudinal data

W. Koo and H. Kim

Statistical Methods in Medical Research, 29(11), 3381-3395.

Statistical Methods in Medical Research
J32

Variational deep clustering of wafer map patterns

J. Hwang and H. Kim

IEEE Transactions on Semiconductor Manufacturing, 33(3), 466-475.

IEEE Transactions on Semiconductor Manufacturing
J31

Bayesian nonparametric joint mixture model for clustering spatially correlated time series

Y. Lee and H. Kim

Technometrics, 62(3), 313-329.

Technometrics
J30

A Bayesian nonparametric mixture measurement error model with application to spatial density estimation using mobile positioning data with multi-accuracy and multi-coverage

Y. Lee, T. Jeong, and H. Kim

Technometrics, 62(2), 173-183.

Technometrics
J29

Fault classification in high-dimensional complex processes using semi-supervised deep convolutional generative models

T. Ko and H. Kim

IEEE Transactions on Industrial Informatics, 16(4), 2868-2877.

IEEE Transactions on Industrial Informatics
J28

A multiscale spatially varying coefficient model for regional analysis of topsoil geochemistry

K. Kim, H. Kim, V. Kim, and H. Kim

Journal of Agricultural, Biological, and Environmental Statistics, 25, 74-89.

Journal of Agricultural, Biological, and Environmental Statistics
2019
C4

Ladder Capsule Network

T. Jeong, Y. Lee, and H. Kim

International Conference on Machine Learning (ICML), pp. 3071-3079, Long Beach, CA, USA, June 2019. (Acceptance rate: 22.6%)

ICML
J27

Spatio-temporal autoregressive model for origin-destination air passenger flows

K. Kim, V. Kim, and H. Kim

Journal of the Royal Statistical Society: Series A, 182(3), 1003-1016.

Journal of the Royal Statistical Society: Series A
J26

Crime risk maps: multivariate spatial analysis of crime data

J. Chung and H. Kim

Geographical Analysis, 51(4), 475-499.

Geographical Analysis
J25

Spatial cluster detection in mobility networks: a copula approach

H. Kim, R. Duan, S. Kim, J. Lee, and G.-Q. Ma

Journal of the Royal Statistical Society: Series C, 68(1), 99-120.

Journal of the Royal Statistical Society: Series C
J24

A practical approach to measuring the impacts of stockouts on demand

S. Kim, H. Kim, and J.-C. Lu

Journal of Business & Industrial Marketing, 34(4), 891-901.

Journal of Business & Industrial Marketing
2018
J23

Modeling the probability of a batter/pitcher matchup event: A Bayesian approach

W. Doo and H. Kim

PLoS ONE, 13(1), e0204874.

PLoS ONE
J22

Functional logistic regression with fused lasso penalty

H. Kim and H. Kim

Journal of Statistical Computation and Simulation, 88(15), 2982-2999.

Journal of Statistical Computation and Simulation
J21

Classification of mixed-type defect patterns in wafer bin maps using convolutional neural networks

K. Kyeong and H. Kim

IEEE Transactions on Semiconductor Manufacturing, 31(3), 395-402 .

IEEE Transactions on Semiconductor Manufacturing
J20

Detection and clustering of mixed-type defect patterns in wafer bin maps

J. Kim, Y. Lee, and H. Kim

IISE Transactions, 50(2), 99-111. (Selected as a featured article and highlighted in the ISE magazine)

IISE Transactions
J19

Application of kernel principal component analysis to multi-characteristic parameter design problems

W. Soh, H. Kim, and B.-J. Yum

Annals of Operations Research, 263, 69-91.

Annals of Operations Research
2017
J18

Hierarchical spatially varying coefficient process model

H. Kim and J. Lee

Technometrics, 59(4), 521-527.

Technometrics
J17

TrailSense: a crowdsensing system for detecting risky mountain trail segments with walking pattern analysis

K. Kim, H. Zabihi, H. Kim, and U. Lee

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 1(3), Article 65. (Presented at UbiComp 2017)

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
J16

Incorporation of engineering knowledge into the modeling process: a local approach

H. Kim, J. T. Vastola, S. Kim, J.-C. Lu, and M. A. Grover

International Journal of Production Research, 55(20), 5865-5880.

International Journal of Production Research
J15

Detection of PVC by using a wavelet-based statistical ECG monitoring procedure

Y. Jung and H. Kim

Biomedical Signal Processing and Control, 36, 176-182.

Biomedical Signal Processing and Control
J14

Early detection of vessel delays using combined historical and real-time information

S. Kim, H. Kim, and Y. Park

Journal of the Operational Research Society, 68(2), 182-191.

Journal of the Operational Research Society
J13

Batch sequential minimum energy design with design region adaptation

H. Kim, J. T. Vastola, S. Kim, J.-C. Lu, and M. A. Grover

Journal of Quality Technology, 49(1), 11-26.

Journal of Quality Technology
J12

An integrated holistic model of a complex process

H. Kim, S. Kim, J. Deng, J.-C. Lu, K. Wang, C. Zhang, M. A. Grover, and B. Wang

International Journal of Advanced Manufacturing Technology, 89(1), 1137-1147.

International Journal of Advanced Manufacturing Technology
2016
C3

Looking back on the current day: interruptibility prediction using daily behavioral features

M. Choy, D. Kim, J.-G. Lee, H. Kim, and H. Motoda

ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp).

UbiComp
C2

Bayesian nonparametric collaborative topic Poisson factorization for electronic health records-based phenotyping

W. S. Lee, Y. Lee, H. Kim, and I.-C. Moon

International Joint Conference on Articial Intelligence (IJCAI).

IJCAI
J11

A multivariate loss function approach to robust design of systems with multiple performance characteristics

W. Soh, H. Kim, and B.-J. Yum

Quality and Reliability Engineering International, 32(8), 2685-2700.

Quality and Reliability Engineering International
J10

Ordinal classification of imbalanced data with application in emergency and disaster information services

S. Kim, H. Kim, and Y. Namkoong

IEEE Intelligent Systems, 31(5), 50-56.

IEEE Intelligent Systems
J9

A new metric of absolute percentage error for intermittent demand forecasts

S. Kim and H. Kim

International Journal of Forecasting, 32(3), 669-679.

International Journal of Forecasting
2015
J8

Adaptive combined space-filling and D-optimal designs

S. Kim, H. Kim, R. W. Lu, J.-C. Lu, M. J. Casciato, and M. A. Grover

International Journal of Production Research, 53(17), 5354-5368.

International Journal of Production Research
J7

Layers of experiments with adaptive combined design

S. Kim, H. Kim, J.-C. Lu, M. J. Casciato, M. A. Grover, D. W. Hess, R. W. Lu, and X. Wang

Naval Research Logistics, 62(2), 127-142.

Naval Research Logistics
2014
J6

Asymptotic optimality of a multivariate version of the generalized cross validation in adaptive smoothing splines

H. Kim and X. Huo

Electronic Journal of Statistics, 8, 159-183.

Electronic Journal of Statistics
J5

A Lipschitz regularity-based statistical model, with applications in coordinate metrology

H. Kim, X. Huo, M. Shilling, and H. Tran

IEEE Transactions on Automation Science and Engineering, 11(2), 327-337.

IEEE Transactions on Automation Science and Engineering
J4

A single interval based classifier

H. Kim, X. Huo, and Jianjun Shi

Annals of Operations Research, 216, 307-325.

Annals of Operations Research
2013
J3

Optimal sampling and curve interpolation via wavelets

H. Kim and X. Huo

Applied Mathematics Letters, 26(7), 774-779.

Applied Mathematics Letters
J2

Dependence maps, a dimensionality reduction with dependence distance for high-dimensional data

K. Lee, A. Gray, and H. Kim

Data Mining and Knowledge Discovery, 26(3), 512-532.

Data Mining and Knowledge Discovery
2012
J1

Locally optimal adaptive smoothing splines

H. Kim and X. Huo

Journal of Nonparametric Statistics, 24(3), 665-680.

Journal of Nonparametric Statistics
2010
C1

Spatiotemporal event detection in mobility networks

T. Au, R. Duan, H. Kim, and G.-Q. Ma

IEEE International Conference on Data Mining (ICDM), 28-37.

ICDM